Marfan Syndrome Decreases Ca<sup>2+</sup> Wave Frequency and Vasoconstriction in Murine Mesenteric Resistance Arteries without Changing Underlying Mechanisms
Bibliographic record
Abstract
BACKGROUND/AIMS: Vascular smooth muscle in Marfan syndrome, a connective tissue disorder caused by mutations in FBN1 encoding fibrillin-1, is associated with decreased tonic contraction. As Ca(2+) waves are tightly associated with vasoconstriction, we hypothesized decreased tonic contraction in Marfan syndrome is due to aberrant Ca(2+) wave signaling. METHODS: Isometric force and intracellular Ca(2+) were measured from second-order mesenteric arteries from mice heterozygous for the Fbn1 allele encoding a cysteine substitution (Fbn1(C1039G/+)). RESULTS: Phenylephrine concentration-dependently induced tonic contraction associated with sustained repetitive oscillations in intracellular [Ca(2+)] in both control and Marfan vessels, although Marfan vessels displayed significantly decreased Ca(2+) wave frequency and decreased number of cells exhibiting waves. Inhibition of sarcoplasmic reticulum Ca(2+) re-uptake by cyclopiazonic acid abolished Ca(2+) waves, dramatically decreasing tonic contraction. Nifedipine significantly reduced Ca(2+) wave frequency and tonic contraction, while the nifedipine-insensitive component was abolished by SKF-96365. Ca(2+) waves and tonic contraction were abolished by 2-aminoethoxydiphenylborate, but were unaffected by ryanodine or tetracaine. CONCLUSION: Phenylephrine-induced Ca(2+) waves underlie tonic contraction in resistance-sized mesenteric arteries and appear to be produced by repetitive cycles of regenerative Ca(2+) release from the sarcoplasmic reticulum. Decreased frequency of Ca(2+) waves in Marfan syndrome appears to be responsible for reduced tonic contraction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".